Publishing with CESSDA archives

For high-quality data with a potential for reuse, we recommend you to assure long-term access by publishing them with a trusted repository, like many of the CESSDA archives. CESSDA archives aim to make the research data accessible with as few restrictions as possible, while at the same time protecting (sensitive) personal data from inappropriate access.

CESSDA archives per country

In the image map below you can see for yourself whether a CESSDA archive is available as a trusted home for your datasets. If you decide to publish your data to one of the CESSDA archives you will have to invest some time and effort to prepare the data. If research data management is a vital part of your work, then the majority of work has already been done on your way.

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Added benefits of a CESSDA repository

As opposed to self-archiving your dataset, publishing your dataset at a CESSDA archive has the great advantage of having expert help within reach. CESSDA research data management experts can help you to increase the comprehensibility, visibility, findability, reusability, longevity and the overall quality of your datasets in the following ways:

At a CESSDA archive, you can deposit your data with the help of a data expert. This expert will advise you on what information is needed to understand your data. Ensuring that your metadata is as rich and complete as possible helps in making sure your data meet the F (Findability) and I (interoperability) in FAIR data management.

In general, you will have to provide the following metadata and data documentation when publishing your data with a CESSDA data archive:*

Short abstract (max. 200-300 words): starting point, purpose and objectives of the research and the main problems addressed in the survey. If the data file is part of the international project, please give some information about it.

Description of target population covered in data file, e.g. Included: The adult residents of R Slovenia, older than 18 years, living on permanent address. Excluded: People living in household without telephone and institutionalized people.

* To ensure findability and interoperability, CESSDA archives work towards standardisation of metadata. DDI and CESSDA Controlled Vocabularies are used for many of the fields mentioned above. Before you start filling in the fields above, contact your data archive because they might have slightly different requirements.

Scientific creditsYou may get scientific credits for a data publication. E.g., in Slovenia, publishing research data in a data archive approved by the Research Funding Agency may lead to gaining the status of a scientific publication. "To reach this status the research study and data in question should meet the following conditions (see ' Study Classification in the ADP' (ADP, 2017a)):

The study should have scientific and methodological excellence;

Relevance is shown for reuse for a wide arrange of practical and theoretical problems;

The data collection has to be a result of a concluded study;

The data collection must fulfil high criteria of quality that are ascertained on the basis of extensive accompanying documentation;

With a combination of data licensing (see 'Data licenses') and access categories (see 'Access categories') CESSDA data archives can control the exact level of access and permitted reuse. In this way, you can make the optimal choice to enhance the reuse potential of your research data whilst simultaneously protecting your participants' identities.

Basic quality checks to ensure the completeness and the understanding of any deposited data, as follows:

Dataset dimension checks: the number of cases and variables are checked against the documentation;

Metadata checks: all variables should have variable labels and all categorical variables should have value labels / the dataset must be comprehensible in association with the documentation given to users;

Data validity checks:

All categorical variables must be checked for out-of-range values/wild codes;

Possible interval variables must be checked for improbable or impossible value.

DANS performs data quality checks of the deposited data and metadata. DANS provides specific instructions for depositing social science data on their website, including an overview of the data requirements which will be checked during the process. See the 'Depositing information' (DANS, 2017a) and a detailed list of the data quality checks (DANS, n.d.).

All data that are deposited are reviewed and processed, for instance all data are checked with respect to anonymity. See the (Norwegian) information on the website of the Norwegian Center for Research Data (NSD, n.d.a).

Detailed quality checks to ensure the completeness and the understanding of any deposited data and documentation, as follows:

Dataset dimension checks: the number of cases and variables are checked against the documentation;

Metadata checks: all variables should have variable labels and all categorical variables should have value labels / the dataset must be comprehensible in association with the documentation given to users;

Data validity checks:

All categorical variables must be checked for out-of-range values/wild codes;

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LOCAL WORKSHOPS

For more in-depth knowledge of local regulations, funder requirements and best practices check our training event calendar for local workshops.
If you are a trainer and would like to organise your own workshop please contact training@cessda.eu.